Active travel to school: literature review - Community Engagement ...

Active travel to school:
literature review
Dr Jan Garrard
July 2011
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Contents
Executive summary _________________________________________________________ 5
Introduction ___________________________________________________________________ 5
Physical activity, active transport and children’s health ________________________________ 5
Health risks associated with active transport to school _________________________________ 6
Active travel to and from school in Australia and the ACT _______________________________ 7
Effectiveness of interventions aimed at increasing children’s rates of active travel to school __ 8
Future directions/innovations for promoting active travel for children in Australia and the ACT 8
Conclusions ____________________________________________________________________ 9
Active travel to school: literature review _______________________________________ 11
1 Introduction _____________________________________________________________ 11
2 Physical activity, active transport and children’s health __________________________ 13
2.1 Health benefits of physical activity and active transport ____________________________ 15
2.1.1 Physical health____________________________________________________________________ 15
2.1.2 Mental health ____________________________________________________________________ 18
2.1.3 Intelligence quotient and educational attainment _______________________________________ 18
2.1.4 Demographic distribution of active transport ___________________________________________ 19
2.2 Health benefits of reduced car use _____________________________________________ 20
2.2.1 Air quality _______________________________________________________________________ 20
2.2.2 Noise pollution ___________________________________________________________________ 20
2.2.3 Climate change ___________________________________________________________________ 21
2.2.4 Community liveability ______________________________________________________________ 21
2.2.5 Children’s independent mobility _____________________________________________________ 22
2.2.6 Traffic congestion _________________________________________________________________ 23
3 Health risks associated with active transport to school __________________________ 25
3.1 Traffic injuries ______________________________________________________________ 25
3.2 Exposure to air pollutants ____________________________________________________ 26
4 Rates of active travel to school in Australia and the ACT _________________________ 27
4.1 Active travel to school in Australia and internationally _____________________________ 27
4.2 Active travel to school in the ACT ______________________________________________ 28
4.2.1 Children’s overall physical activity levels _______________________________________________ 28
4.2.2 Children’s participation in active transport _____________________________________________ 29
5 Potential for mode shift to active travel to school: the role of trip distance __________ 29
6 Effectiveness of interventions aimed at increasing children’s rates of active travel to
school ___________________________________________________________________ 32
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6.1 Evidence reviews ___________________________________________________________ 32
6.2 Recent evaluations of active school travel interventions ____________________________ 33
6.2.1 Australia _________________________________________________________________________ 33
6.2.2 International AST programs _________________________________________________________ 36
6.3 Summary of the impacts of active transport initiatives in schools ____________________ 36
6.4 Aggregate level change ______________________________________________________ 37
7 Understanding the influences on active travel to school _________________________ 38
7.1 Social-ecological model of active school travel ____________________________________ 38
7.2 Perceived benefits/barriers model of active school travel ___________________________ 40
8 Future directions/innovations for promoting active travel for children in Australia and
the ACT __________________________________________________________________ 42
9 Conclusions _____________________________________________________________ 45
References _______________________________________________________________ 46
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List of acronyms and abbreviations
ABS Australian Bureau of Statistics
AT Active transport
LTPA Leisure-time physical activity
MET Metabolic equivalent of task
ACT Australian Capital Territory
MVPA Moderate to vigorous physical activity
WSB Walking school bus
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Executive summary
Introduction
Physically active children are healthier, happier and more socially connected than children
who have more sedentary lifestyles, yet many Australian children do not meet
recommended levels of physical activity. ‘Incidental’ exercise, including active transport, can
substantially contribute to overall levels of physical activity yet it has declined markedly in
recent decades. Current levels among children and young people in Australia (and the ACT)
are now less than half the 1970 levels.
The current focus on ‘active living’ has led to a growing recognition of the potential for
incidental forms of physical activity. Active transport provides an activity that is continuous,
expends sufficient energy, can be performed by most children, does not appear to displace
other forms of physical activity and is not principally performed by children who are already
active. Increasing children’s active travel is likely to result in net gains in the overall levels of
physical activity, and in the proportion of children achieving the recommended levels of
physical activity.
A number of high-income countries and cities have successfully reversed the trend of
steadily increasing car travel by children and young people, while a range of Australian
government policies and programs at federal, state, territory and local levels to increase
active travel for children and adults have been developed and implemented. Evaluation of
these initiatives in Australia and overseas indicates variable effectiveness, and highlights the
learning curve required to achieve the high levels of active travel among children in several
European and Asian countries and cities. To assist the evaluation process, this report
provides an evidence-based summary of:
� The relationships between physical activity, active transport and children’s health.
� Rates of active travel to and from school in Australia and the ACT.
� The effectiveness of interventions aimed at increasing children’s rates of active
travel to school.
� Future directions for promoting active travel for children in Australia and the ACT.
Physical activity, active transport and children’s health
The child health benefits of moderate-to-vigorous physical activity (MVPA), including active
transport, encompass physical, mental and social health in the form of:
� Healthy child development (bone, muscle, joint health): Moderate to vigorous
weight-bearing physical activity during childhood is essential for optimal skeletal,
joint and muscle growth. While no studies were found that focused specifically on
active transport, walking is a weight-bearing form of physical activity with cycling
less so (depending on cycling style and the terrain covered).
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� Aerobic fitness: Cycling and walking to school improves cardiovascular fitness among
young people, particularly girls.
� Healthy weight: Indirect evidence points to a relationship between active transport
and overweight/obese children, but the available evidence is not definitive.
Evidence indicates that the contribution of active transport to maintaining healthy
weight depends on walking or cycling trip distances.
� Mental health: There is evidence of an inverse association between physical activity
and some measures of child mental health, but there appear to be no studies of
active transport and mental health.
� Intelligence quotient and educational attainment: There is consistent evidence of a
significant positive relationship between physical activity and cognitive function, and
more recently between aerobic power, intelligence quotient (IQ) and educational
attainment. Studies were not specifically of active transport.
The co-benefits of active transport not associated with leisure-time physical activity (LTPA)
include:
� More equitable distribution of physical activity across some key population
demographic segments. Adolescents, particularly females, are more likely to meet
physical activity guidelines if they travel actively to school.
� A range of physical, psychological and social health benefits associated with reduced
motor vehicle use (due to replacing car trips with active trips). These include reduced
air and noise pollution, and reduced traffic injuries.
� Improvements in community liveability, traffic congestion, environmental
sustainability, climate-change abatement and reduced dependency on nonrenewable
energy sources that impact on all community members, including
children.
Health risks associated with active transport to school
The health risks associated with active transport are (i) the risk of traffic injury, (ii) exposure
to air pollutants and (iii) risk of injury (in common with other forms of physical activity such
as sport and play). Pedestrian and cyclist injuries are often compared with risk of injury as a
car passenger as they are alternative forms of transport.
Absolute levels of risk of child pedestrian and cyclist fatalities in Australia are low, 1 although
child pedestrians and cyclists have a greater risk of injury than car passengers per unit of
exposure (ie. distance or time travelled). Child pedestrian and cyclist fatality rates (per km
travelled) in OECD countries with high rates of walking and cycling are about one-quarter of
the rates in countries with low rates of these activities (such as Australia). This data
indicates the considerable potential to improve child pedestrian and cyclist safety in
Australia.
1 Child pedestrian fatalities 0.86 per 100,000 child population; and child cyclist fatalities 0.39 per 100,000 child
population.
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Modelling studies show that if a substantial share of trips by motorised transport is
transferred to walking or cycling, the total number of road traffic crashes (including multivehicle
and single-vehicle car crashes, as well as pedestrian-car and cyclist-car crashes) is
reduced. More commonly, rates of pedestrian, cyclist and overall road traffic injuries are
observed to decline as active travel mode share increases.
While risk-benefit analyses demonstrate the health benefits of cycling for adults outweigh
the risks, no comparable studies for children or for walking were found.
Active travel to and from school in Australia and the ACT
In contrast to several European and Asian countries, children’s rates of active travel to
school and other destinations in Australia and the ACT are low and declining. In the ACT in
1970, more students travelled to school or university by bicycle (13.1%) or walking (46.8%)
than by car (12.1%) 2 (Australian Bureau of Statistics 1975). By 1997, only 29.7% of students
walked (22.2%) or cycled (7.5%) to full-time education (Brown and Nairn 1997). The decline
over time, and current rates of active travel to school, are similar to those in Victoria (27%
of students aged 5-12 years), although higher than in the Greater Sydney Metropolitan Area
(22% of primary school students) (Garrard 2010).
In 2006, 30.5% of Year 6 students in the ACT 3 walked or cycled to school 4 (Population Health
Research Centre ACT Health 2007). Care needs to taken in comparing this rate of active
travel to school with the 1997 figure (29.7%) due to differences in the study population and
the measure of active transport. Preliminary analysis of 2009 data indicates a statistically
significant decline between 2006 and 2009 (30.5% and 24.3% respectively) in the proportion
of Year 6 students walking or cycling to school every day (ACT Health, preliminary analysis of
2009 ACTPANS data).
Cross-country comparative data show large differences in active travel to school 5 which are
not accounted for by greater trip distances to school in countries with low rates of active
travel. In many high active travel countries, children walk and cycle to school for trip
distances that are predominantly made by car in countries such as Australia.
There is also greater international variation in cycling rates than in walking rates which may
account for a large part of the international variations in overall rates of active transport. In
countries such as Australia, car trips largely replace walking trips for distances greater than 1
km, while bicycle trips are more common than car trips for distances up to about 4 km in
high active transport countries.
2
Full-time students aged 5 years and over.
3
These data are for grade 6 students only, but levels of active travel among young people in Australia show
little variation between grades 4 and 8 (ref).
4
Five times in a typical week.
5
For example, 86% in the Netherlands, 71% in Denmark, 71% in Germany compared with 13% in the USA, 15%
in Canada and 48% in the UK.
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Active school travel programs in Australia have also been more successful in increasing
walking rather than cycling to school. This trend indicates that cycling to school will require
additional attention if Australia is to move towards the high rates of active travel to school
for short to medium distance trips that occur in several affluent European and Asian
countries.
Effectiveness of interventions aimed at increasing children’s rates of active travel to
school
Active school travel programs typically include some combination of:
� Special walking or cycling promotion days.
� A program of pedestrian and cycle training for children.
� Secure bicycle parking.
� Activities as part of the curriculum to promote the benefits of sustainable transport.
� Physical changes to the streets around the school, such as 40 km/h limits, traffic
calming, pedestrian crossings and bicycle lanes.
� Developing a school travel policy and/or home-school agreement.
Recent evidence reviews indicate that not all programs achieve small-to-moderate increases
in rates of active travel to school. There has been little systematic assessment of the reasons
for variable program impacts although, based on limited process evaluation data to date,
the determinants of success are likely to include factors associated with schools and their
social, cultural and built environments, program type and quality of implementation.
Active travel programs are often successful in participating schools, although there is little
evidence of an overall mode shift to active travel to school in countries with low rates of
active travel.
Future directions/innovations for promoting active travel for children in Australia and the
ACT
The evidence reviewed in this report indicates that in several countries and regions
(England, Scotland, Victoria, NSW and the ACT), population levels of active travel to school
have not changed despite programs with impressive impacts in some participating schools
and for special events (eg walk/ride to school days and the Brisbane City Council Active
School Travel program). It is therefore evident that carefully planned and well-implemented
behaviour change programs are a necessary but not sufficient condition for population-level
change in school travel modes.
Strategic planning and a systems approach are required to move towards the levels of active
travel to school enjoyed by a number of other high-income countries. Denmark, Germany,
the Netherlands and Japan provide models of implementing broad-based policy packages
that make active travel to school a convenient, safe travel mode. Effective active transport
policy models are not restricted to the high active travel countries in Europe and Asia.
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Relatively high rates of active travel to school have been achieved in a small number of
towns and cities in the USA.
The greatest potential for increasing rates of active travel to school lies in encouraging more
young people to walk up to about 1 km and to cycle up to about 5 km. With the right
conditions, policies, education and encouragement, more children would walk or cycle to
school and to other neighbourhood destinations. Strategies to increase active travel to
school, which incorporate school-based programs with area-wide and population-wide
strategies for increasing active travel in the wider community, could include the following
elements:
� Setting goals and targets (eg an increase of 5 percentage points in the walking and
cycling mode share of travel to education in a 5-year period 6,7 ).
� Specifying components of the strategy (eg incorporating the 4Es of Education,
Encouragement, Engineering, and Enforcement).
� Well-defined ‘program logic’ (ie Are we doing the right things? Is the intervention
‘dose’ appropriate? Is the program reach adequate?).
� Identify partners, responsibilities and resources (eg who is responsible for each
component?).
� Evaluation/monitoring (eg including measures of travel to school in school data
collection systems).
The key health promotion strategies of community participation, advocacy and intersectoral
partnerships will also be important in achieving these goals. Many government
sectors and levels have a role in increasing children’s use of healthy and sustainable
transport modes for the many short-to-medium trips that typify children’s travel in urban
areas.
Conclusions
This report demonstrates that increasing levels of car use are the predictable outcome of
transportation policies that promote car use and constrain walking and cycling, and not the
inevitable by-product of low-density suburban living in affluent countries. Changes can be
achieved through programs such as Safe Routes to School, Walking School Bus, School
Travel Planning and Walk/Ride to School events. These initiatives need to be complemented
by area-wide improvements that create supportive environments for active travel. The
experiences of overseas countries, cities and municipalities provide a model for sustainable
transport planning aimed at increasing active travel to school in the ACT.
6
This is approximately the rate at which walking and cycling to education have declined in the last 40 years in
Victoria.
7
The recent White House Task Force on Childhood Obesity Report to the President (Solving the problem of
childhood obesity) set a target of an increase in bike/walk trips to school in the USA of 6.5 percentage points by
2015.
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While implementing and assessing active travel initiatives in participating schools is
important, key questions to consider include (i) the program and contextual factors that
shape the effectiveness of interventions; (ii) the sustainability of change; (iii) the reach of
active travel initiatives; and (iv) the role of supportive community-wide measures. Public
health strategies in areas such as tobacco control, road safety and child immunisation are
successful because they achieved measurable improvements at the population level and not
just in selected schools or communities. Consequently, the well-documented benefits of
active travel will be realised when measurable change occurs at the population level.
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Active travel to school: literature review
1 Introduction
Physically active children are healthier, happier and more socially connected than children
who have more sedentary lifestyles (US Department of Health and Human Services 2008;
WHO 2008), yet data from the 2007 Australian Children’s Nutrition and Physical Activity
Survey shows only 32% of Australian children aged 9-16 years meet the recommended
levels 8 of moderate to vigorous physical activity (MVPA) (Department of Health and Ageing
2008). Additional pedometer data showed the majority of Australian children aged 9-16 did
not meet the recommended number of steps per day (15,000 for boys and 12,000 for girls),
and this number declined rapidly with age (only 13% of boys aged 14-16 years and 16% 9 of
girls aged 14-16 met the recommended number of steps) (Department of Health and Ageing
2008).
Substantial changes in Australian lifestyles, urban environments and transport systems have
led to changed physical activity patterns among children in recent decades (Olds et al 2007).
Active transport 10 has particularly declined dramatically in countries such as the US, UK and
Australia where car travel has become the predominant form of personal mobility (Salmon
et al 2005; van der Ploeg et al 2008). These changes are not primarily due to increased travel
distances to school as they have occurred for all trip distances, including those considered
feasible for walking (up to 1 km) and cycling (up to 5 km) (see Section 5).
In 1970, more students in the ACT travelled to school or university by bicycle (13.1%) or
walking (46.8%) than by car (12.1%) 11 (Australian Bureau of Statistics 1975), but by 2009,
preliminary data analysis indicated only 24.3% of Year 6 students 12 walked or cycled to
school 13 (preliminary analysis of 2009 ACTPANS data, ACT Health).
Active travel to school is also associated with active travel to other destinations (Dollman
and Lewis 2007), making walking or cycling to school indicative of wider use of active travel
modes. Increasing numbers of Australian children are therefore missing out on incidental
forms of physical activity such as active travel to school and other neighbourhood
destinations that were once an integral part of daily life. The decline in active transport has
not been accompanied by increased participation in sport and active recreation which has
remained relatively steady between 2000 and 2009 (Australian Bureau of Statistics 2009)).
8
Accumulated at least 60 minutes of MVPA on each of the four days sampled.
9
The higher percentage for girls is due to the lower recommended number of steps for girls.
10
Active transport refers to travel between destinations by walking, cycling or other non-motorised modes
(National Public Health Partnership 2001).
11
Full-time students aged 5 years and over, usual method of travel to education.
12
These data are for Year 6 students only, but levels of active travel among young people in Australia show
little variation between Years 4 and 8.
13 Five times in a typical week.
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While it is difficult to accurately measure all forms of children’s physical activity, and
comprehensive data from longitudinal surveys are not available, it is likely that substantial
reductions in incidental forms of physical activity are contributing to a decline in children’s
aerobic fitness (Olds et al 2007).
Until recently, promoting physical activity for children has focused on increasing children’s
participation in sport and exercise programs. (Dobbins et al 2009). However, very few
countries have succeeded in increasing physical activity levels in the overall child population
through policies, programs and campaigns aimed at encouraging more children to
participate in leisure-time physical activities such as sport and exercise. Lack of populationlevel
impact for these strategies has led to a shift in focus for physical activity promotion
from ‘deliberative’ leisure-time sport and exercise programs to ‘incidental’ activity through
active living (Sallis et al 2006).
Active transport is a key component of active living, and the evidence base for the ‘health
through physical activity’ benefits of active transport is growing. Modelling of physical
activity patterns in Australian adults demonstrates the potential for relatively small (and
potentially achievable) increases in active travel to impact on the proportion of Australians
who are adequately active. If people who are currently classified as inactive walked or
cycled for an additional 20 minutes three times per week, the proportion of adequately
active Australian adults would increase from 57% to 72% (Garrard et al 2011). Consequently,
the public health potential for active transport is large, even at modest amounts and
frequency of activity, and especially if currently inactive people adopt some degree of
walking or cycling.
Equivalent modelling has not been conducted for children in Australia, but the results are
likely to be similar to those for adults. For example, studies in the UK report that adolescent
girls (a population segment that has low levels of leisure time physical activity) are six to
eight times more likely to meet recommended levels of physical activity if they travel
actively to school (Smith et al 2008; Voss and Sandercock 2010). These, and other findings,
indicate that active transport does not ‘displace’ other forms of physical activity and is not
undertaken principally by children who are already active (Davison et al 2008). Rather,
increases in children’s active travel are likely to result in net gains in children’s levels of
physical activity and in the proportion of children achieving recommended levels of physical
activity (Davison et al 2008; Voss and Sandercock 2010).
A number of industrialised countries and cities have successfully reversed the trend of
steadily increasing car travel by young people. The proportion of the total distance travelled
by 10-14 year-olds using active modes is 33.5% in the Netherlands, 14.4% in Switzerland and
13.8% in Germany. In contrast, only 4.6% of the total distance travelled by young people in
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Melbourne 14 is undertaken using active modes (Christie et al 2004; Ironmonger and Norman
2007). As discussed in Section 5, these differences are not primarily due to longer trip
distances (including to school) in Australia, as many of the active trips made by children in
high active travel countries are for trip distances that are predominantly made by car in
Australia and the USA.
Children in countries that have successfully reversed unsustainable and unhealthy increases
in rates of driving children to school and other destinations achieve high levels of physical
activity ‘incidentally’, at low cost, without children and/or their parents having to find the
time, motivation and resources to participate in organised sports, exercise or fitness
programs. Active transport as a form of incidental activity has a number of co-benefits not
associated with the more ‘deliberative’ forms of leisure-time physical activity as illustrated
in Figure 1 and Table 2.
A number of Australian government policies and programs at federal, state, territory and
local levels have been developed and implemented with the aim of increasing active travel
for children and adults. Evaluation of these initiatives in Australia and overseas indicates
wide variations in effectiveness and highlights the learning curve required to achieve the
high levels of active travel among children that occurs in several other high-income
countries and cities.
This report therefore provides an evidence-based summary of:
� The relationships between physical activity, active transport and children’s health.
� Rates of active travel to and from school in Australia and the ACT.
� The effectiveness of interventions aimed at increasing children’s rates of active
travel (principally to school, which has been the focus of nearly all active travel
interventions for children).
� Future directions/innovations for promoting active travel for children in Australia
and the ACT.
This report draws on Australian and international research, evaluation and current practice,
with ACT data included when available. The focus is on primary school aged children (5-12
years), with older ages included when the data covers a wider age range (eg 10-14 years).
The generic term ‘travel to school’ refers to travel to and from school. ‘Active travel’ and
‘active transport’ refer principally to walking and cycling, as this is the focus of most
research into children’s use of active transport.
2 Physical activity, active transport and children’s health
The child health benefits of moderate to vigorous physical activity (MVPA) encompass
physical, mental and social health in the form of:
14 Melbourne data has been used in the absence of Australian national data. The Melbourne data is for 0-14
year-olds in the Melbourne Statistical Division, 1994-1999.
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� Healthy child development (bone, muscle, joint health).
� Aerobic fitness.
� Healthy weight.
� Mental health.
� Social wellbeing.
� Intelligence quotient (IQ).
� Educational attainment.
The co-benefits of active transport not associated with leisure-time physical activity (LTPA)
include:
� More equitable distribution of physical activity across some key population
demographic segments.
� A range of physical, psychological and social health benefits associated with reduced
motor vehicle use (due to the replacement of car trips with active trips).
� Improvements in community liveability, environmental sustainability, climatechange
abatement and reduced dependency on non-renewable energy sources that
impact on all community members (including children).
The multiple health and social benefits of active transport are summarised in Figure 1, and
evidence in each of these areas is briefly reviewed.
Physical
health
Mental
health
Increased
physical
activity
IQ and
Educational
attainment
Demographic
distribution of
PA
Benefits of
active
transport
Air
quality
Noise
pollution
Rduced car
use
Climate
change
Community
liveability
Traffic
congestion
Figure 1: Health and health-related benefits of active transport for children
The Australian Department of Health and Ageing (2004) recommends that children should
accumulate at least 60 minutes (and up to several hours) of MVPA each day. Moderateintensity
physical activity is defined as between 3-6 METs, 15 or 3-6 times the energy
expenditure at rest (Ainsworth et al 2000), with walking at the lower end of the range and
cycling, which is about twice the intensity of walking, at the top end of the range.
Walking and cycling provide physical activity which can be performed by most adults and
children that is continuous and of sufficient intensity (Garrard et al 2011). Research into
15 The Metabolic Equivalent of Task (MET) expresses the energy expenditure of physical activities as multiples
of the resting metabolic rate; with 1 MET defined as the metabolic rate at rest.
14

active transport as a form of MVPA is relatively recent, and while much of the evidence
reviewed below is for MVPA in general, many of the findings may also apply to active
transport. Direct evidence of the health benefits of active transport as a form of MVPA is
also used whenever possible.
2.1 Health benefits of physical activity and active transport
2.1.1 Physical health
Healthy child development (bone, muscle, joint health)
Moderate to vigorous weight-bearing physical activity during childhood is essential for
optimal skeletal, joint and muscle growth. Physical activity creates higher bone density and
bone mineral content which are vital for protecting against osteoporosis in later life
(Matthews et al 2006). While the benefits of weight-bearing physical activity for children are
well documented, no studies that focused specifically on active transport as a form of
weight-bearing physical activity were found. However, walking is a weight-bearing form of
physical activity while cycling depends on the style (eg standing up/sitting down) and terrain
covered.
Aerobic fitness
Several recent studies have reported significantly higher levels of cardiovascular fitness
among young people who cycle to school (Cooper et al 2006; Cooper et al 2008; Andersen
et al 2009; Voss and Sandercock 2010). Evidence for the relationship between improved
cardiovascular fitness and walking to school is less consistent, possibly due to the higher
MET value for cycling compared with walking. For example, Andersen et al (2009) found that
adolescents who cycle to school (almost two-thirds of the participants in the Danish Youth
and Sports Study) had higher aerobic power (4.5% for girls and 5.9% for boys) than both
walkers and passive travellers.
In a large UK study, Voss and Sandercock (2010) examined the likelihood of being classified
as ‘fit’ according to travel mode (with ‘passive transport users’ as the reference group).
Consistent with other studies, the greatest benefits were for cycling compared with walking,
and for girls compared with boys. Girls were nearly eight times more likely to be classified as
‘fit’ if they cycled to school after adjusting for covariates 16 including other forms of physical
activity. The finding of a marked improvement in fitness for girls who walk or cycle to school
reflects the rapid deline of leisure-time physical activity among adolescent girls in countries
such as the UK and Australia (Department of Health and Ageing 2008).
Healthy weight
The proportion of overweight and obese children aged 5 – 17 years increased from 20.8% in
1995 to 24.9% in 2007-08 (Australian Bureau of Statistics 2009). Obesity in young people is
16 A covariate is a variable that is possibly predictive of the outcome under study. A covariate may be of direct
interest or it may be a confounding or interacting variable.
15

associated with psychological problems, inappropriately fast growth and development,
abnormal lipid/body fat profile, high blood pressure and abnormal glucose
tolerance/metabolism (Kelty et al 2008; The Obesity Society nd). Obesity during childhood,
particularly adolescence, is related to obesity as an adult and the associated increased risks
of developing chronic diseases as an adult (The Obesity Society, nd).
Indirect evidence points to a relationship between active transport and overweight/obese
children, but the available evidence is not definitive. Cross-country comparative data shows
an inverse relationship between distance walked and cycled per child (10-14 years) per year
and being overweight/obese (see Table 1 and Figure 2), while studies within countries such
as Australia with low rates of active travel show no consistent relationship (Booth et al 2006;
Davison et al 2008; Lee et al 2008; Voss and Sandercock 2010). This may be due to the
limited range of energy expenditure on active travel in Australia (ie children in the highest
active travel categories in Australia have low levels of active travel compared with children
in several European and Asian countries).
Children in European and Asian countries with high active travel rates frequently cover
relatively large distances by foot or bicycle (see Tables 1 and 3) which contributes to energy
expenditure and maintenance of a healthy weight. Australia’s low cycling rates potentially
lead to lower energy expenditure than countries where children have relatively high rates of
cycling to school. Consistent with this explanation, the Kiel Obesity Prevention Study in
Germany found that active commuting to school did not affect Body Mass Index (BMI) or fat
mass, but there was a decrease in fat mass for longer walking or cycling trip distances
(Landsberg et al 2008). Active commuting comprised 28.4% of overall physical activity.
In population terms, active transport cannot prevent all young people from becoming
overweight, or provide a stand-alone intervention for weight loss. However, it will probably
contribute to reducing the prevalence of overweight and obese young people.
16

Table 1: Distance walked and cycled per child (10-14 years) per year (kilometres)
Country Distance walked per
child per year
(kilometres)
(Source: Christie et al, 2004)
Distance cycled per
child per year
(kilometres)
USA 123 n/a 0.8 17
UK 396 79 6.8
NZ n/a 232 n/a
Norway 550 370 9.7
Sweden 275 424 7.4
Germany 431 518 13.8
Switzerland 773 535 14.4
Netherlands 180 2200 33.5
Melbourne 18 182 26 4.6
Figure 2: Children’s active travel distance and overweight/obesity
Proportion of total
distance travelled
using active modes
(%)
(Melbourne Statistical Division travel data included in absence of Australian national data
for children’s active travel distance)
(Sources: Christie 2004; International Obesity TaskForce 2009)
17 Walking only - cycling rates are not included in US data because they are very low.
18 Melbourne Statistical Division (Greater Melbourne Metropolitan Area), children aged 0-14 years, VATS 1994-
99 average (Ironmonger and Norman 2007).
17

2.1.2 Mental health
Rates of mental health problems in Australian children and adolescents are increasing
(Australian Bureau of Statistics 2007). Several cross-sectional studies have demonstrated
inverse associations between physical activity and psychological distress in adolescents
(Hamer et al 2009), although there is limited research on physical activity and psychological
factors in younger children (≤ 12 years of age), or from longitudinal studies or intervention
studies.
A recent study involving younger children found television and screen entertainment (TVSE)
time and physical activity were independently associated with children’s Strengths and
Difficulties Questionnaire (SDQ) total difficulties score after adjustment for age, gender,
index of deprivation, single-parent status, chronic medical conditions and various dietary
indicators. The SDQ incorporates subscales of hyperactivity, emotional symptoms, conduct
problems and peer problems (Hamer et al 2009). A numbers of authors note the crosssectional
nature of most studies in this area cannot rule out the possibility of bias from
unmeasured variables.
2.1.3 Intelligence quotient and educational attainment
A number of studies have reported that higher aerobic power among young people is
associated with increased IQ, improved cognitive functioning and higher educational
attainment (Sibley and Etnier 2003; Åberg et al 2009).
A recent landmark study involving all Swedish men born between 1950 and 1976 who were
enlisted for military service at age 18 (N = 1,221,727) found that cardiovascular fitness,
measured by ergometer cycling, was positively associated with intelligence (Wechsler Adult
Intelligence Scale), school achievement and subsequent socioeconomic status after
adjusting for relevant confounders (Åberg et al, 2009). An earlier meta-analysis of the
relationship between physical activity and cognitive functioning in children found a
significant positive relationship between physical activity and cognitive function (Sibley and
Etnier 2003).
Consistent with these findings, a review of “Physical Education, Physical Activity and
Academic Performance” conducted by the US Active Living Centre 19 concluded that:
� Studies consistently show that more time in physical education and other schoolbased
physical activity does not adversely affect academic performance.
� In some cases, more time in physical education leads to improved grades and
standardised test scores.
� Physically active and fit children tend to have better academic achievement.
� Evidence links higher levels of physical fitness with better school attendance and
fewer disciplinary problems.
19 http://www.activelivingresearch.org/files/Active_Ed_Summer2009.pdf
18

� There are several possible mechanisms by which physical education and regular
physical activity could improve academic achievement, including enhanced
concentration skills and classroom behaviour.
While there is no direct evidence that active travel to school improves cognitive functioning
or educational attainment, the link between active travel and aerobic fitness described in
Section 2.1.1 suggests that active travel as a form of MVPA might contribute to these
cognitive and educational benefits.
2.1.4 Demographic distribution of active transport
There are indications, both in Australia and internationally, that active transport is a more
socially inclusive form of MVPA than leisure-time physical activity due to more evenly
spread participation across demographic segments of the population. This is particularly the
case for age and gender of Australian children. Data from the Australian Children’s Nutrition
and Physical Activity Survey indicate that active travel does not decline with age and has
similar participation rates for girls and boys at most age levels as opposed to sport and play
(Figure 3). These age- and gender-specific physical activity patterns are consistent with the
findings described in Section 2.1.1 which show that girls (and adolescent girls in particular)
are several times more likely to meet physical activity guidelines if they travel actively to
school (Smith et al 2008; Voss and Sandercock 2010).
The more socially inclusive, population-wide participation in physical activity associated with
active travel in high active travel countries might also help to explain the inverse
relationship between active travel and obesity (see Figure 2).
Figure 3: Age and gender-related patterns in MVPA and some of its components [free play, sport
and active transport (AT)].
(Source: Department of Health and Ageing 2008)
19

Another key area of distinction between leisure-time physical activity and active transport is
the range of co-benefits associated with reduced motor vehicle use when active transport
trips replace car trips.
2.2 Health benefits of reduced car use
2.2.1 Air quality
Motor vehicles are a major source of air pollution in most cities and contribute up to 80% of
air pollution (depending on pollutant) in large cities such as Melbourne and Sydney (Bureau
of Transport and Regional Economics 2005). Between 900 and 4500 cases of cardiovascular
and respiratory disease occurred in Australia in 2000 due to motor vehicle related air
pollution costing between $0.4 billion and $1.2 billion. Air pollution caused by motor
vehicles also accounted for between 900 and 2000 premature deaths with an estimated cost
of between $1.1 billion and $2.6 billion (Bureau of Transport and Regional Economics 2005).
These premature deaths, labelled ‘the silent road toll’, are comparable to the number of
people killed in road crashes (1368 in Australia in 2010).
Motor vehicle related air pollution also affects children, with deficits in lung function growth
showing a linear relationship with air pollution (Gauderman et al 2004). A study of proximity
to engine exhaust emissions in Great Britain, and the link with children dying from
cancer/leukemia, found maximum effects at short (0.1–0.5 km) effective ranges, tapering to
neutral after 3 km. Over 24% of child cancers are attributable to these exposures with roads
exerting the major effect (Knox 2006).
The Australian Institute of Health and Welfare (2010) developed a method for estimating
the contribution of air pollution to asthma hospitalisations. The study, which used the
adjusted results of Melbourne in 2006 as a case study, found:
� Approximately 3% of all asthma hospitalisations in Melbourne in 2006 were related
to exposure to nitrogen dioxide (60% due to motor vehicle emissions).
� Approximately 4% of asthma hospitalisations of 0–14 year olds were related to
particulates in the air (30% due to motor vehicle emissions).
2.2.2 Noise pollution
Environmental noise impacts on people’s lives through annoyance, sleep disturbance,
reduced work or school performance, stress and anxiety, reduced enjoyment of home life
and other physical health effects. Exposure to noise leads to cognitive impairment in
children and affects their ability to study and learn (World Health Organization: Regional
Office for Europe 2011).
Surveys and noise measurements conducted by the Victorian Environmental Protection
Authority (EPA) in late 2006 at 50 sites across the inner, middle and outer suburbs of
Melbourne found that transport is the main (and loudest) source of noise pollution. Seventy
20

percent of people hear traffic noise in their homes and over one million Victorians are
annoyed by it (Environmental Protection Authority 2007).
Traffic noise was also identified as a key community concern for Australians with
‘dangerous/noisy driving’ the most frequently reported perceived neighbourhood problem
with crime or nuisance. These concerns were ahead of vandalism/graffiti, housebreakings,
drunkenness, louts/gangs, car theft and illegal drugs (Australian Bureau of Statistics 2010).
2.2.3 Climate change
Transport is a significant and growing source of the greenhouse gas emissions that
contribute to climate change. It accounts for 14.6% of total Australian emissions, having
risen by 29% between 1990 and 2008 (Department of Climate Change and Energy Efficiency
2010). The transport sector contributes a significantly greater proportion to total emissions
in the ACT than at the national level, and accounted for 23% of total ACT greenhouse gas
emissions in 2008 (Department of the Environment, Climate Change, Energy and Water,
2010).
The environmental consequences of climate change, which include sea-level rise, degraded
air quality and extreme weather events (resulting in droughts, floods, heat waves, more
intense hurricanes and storms) affect human health both directly and indirectly. The health
effects of climate change (USA Interagency Working Group on Climate Change and Health
2009 nd) include:
� Heat-related mortality and morbidity.
� Injuries.
� Drowning.
� Vector, food and water-borne diseases.
� Food and water shortages and malnutrition.
� International conflict.
� Cardiovascular disease, stroke and cancer.
� Exacerbation of respiratory diseases such as asthma.
� Respiratory allergies and airway diseases.
� Mental health and stress-related disorders.
2.2.4 Community liveability
Children are particularly vulnerable to the impacts of high levels of car use in urban areas.
The provision of road space to enable high volume, high speed car travel comes at a cost to
other road users and local residents in terms of community disruption, noise pollution,
social isolation, urban sprawl and restrictions on children’s independent mobility,
21

opportunities for outdoor play and social interactions (Dora and Phillips 2000; Social
Exclusion Unit 2003; Ewing et al 2006; Carver et al 2008; Carver et al 2008a; Litman 2009).
Appleyard’s original research, which found heavy traffic is associated with reduced streetbased
activities and social interactions between neighbours (Appleyard and Lintell 1980),
has now been replicated in other settings (Bosselmann and MacDonald 1999; Hart 2008). In
terms of social interactions among children, ’socialising with friends‘ was one of the three
most frequently cited reasons for liking walking to school based on a survey of primary
school students conducted as part of the evaluation of the Victorian Ride2School program
(Garrard et al 2009).
There is consistent evidence that parents restrict their children’s walking and cycling to
school because of injury concerns in countries like Australia (Garrard et al 2009; McDonald
et al 2010). These risk perceptions can contribute to what Horton (2007) refers to as the
’fear of cycling‘. Jacobsen et al (2009) also describe how motor vehicle domination of
transport infrastructure creates fear of walking and cycling, leading to declining levels of
active transport, and setting in train a vicious cycle of continuing retreat of cyclists and
pedestrians from public spaces increasingly dominated by cars.
In contrast, the injury risks posed by increasing numbers of motor vehicles in urban areas in
the Netherlands during the 20 th century led to a comprehensive package of measures to
curb motor vehicle use in urban areas and improve pedestrian and cyclist safety. These
included extensive, high-quality cycling infrastructure‘ and establishment of the legal
responsibility of car drivers to avoid collisions with cyclists and pedestrians. The Dutch
approach is: “cyclists are not dangerous; car drivers are: so car drivers should take the
responsibility for avoiding collisions with cyclists” (Ministry of Transport Public Works and
Water Management 2009). These measures have contributed to a cycling (and walking)
environment that is both safe and pleasant, and where parents can confidently allow their
children to walk and cycle independently.
There is also evidence that the more compact, permeable urban designs that support cycling
and walking lead to crime reduction through increased street activity and ’natural
surveillance‘ (Cozens et al 2005). In a detailed study in the UK, Hillier and Sahbaz (2006)
concluded that reduced risk of crime arises from “the ordinary co-presence of people that
everyday movement and activity brings.” This improves personal security for all community
members.
2.2.5 Children’s independent mobility
An under-recognised consequence of excessive car use in urban areas is parental
curtailment of children’s independent mobility which is the freedom to move about
unaccompanied within their neighbourhood or community (Zubrick et al 2010). A number of
studies have documented substantial declines in children’s independent mobility over time
in countries such as the UK and Australia. In 1971, nearly three-quarters of 7-11 year-old
22

children in England were allowed to cross roads alone. By 1990 the proportion had fallen to
about a half (Hillman 1993).
The reduction in independent mobility was even greater for cycling on the roads. Between
1971 and 1990, child bicycle ownership increased from two-thirds to nine in ten, but the
proportion of children who said they were allowed to use them on the roads declined from
two-thirds to a quarter (Hillman 1993). Children’s independent mobility in England has
decreased further in recent times. In 2002, 78% of 7 to 10 year olds were accompanied by
their parents to school, increasing to 85% in 2006 (Department for Transport 2008).
Children’s outdoor autonomy also varies across countries. In the early 1990s, German
children had much more travel freedom than their English or Australasian counterparts. For
example, 90% of German 9 year olds were allowed to cross roads alone compared with 50%
of English or Australasian children (Hillman et al 1990; Tranter 1996).
Independent mobility plays an important role in the development of children’s spatial,
motor and analytic skills, environmental competence, social and emotional development
and resilience (Prezza et al 2005; Malone 2007; Zubrick et al 2010; Badland et al 2011). It
has also been argued that children have a right to move about safely in the outdoor
environment. This right has been increasingly eroded by systematically prioritising the needs
of motorists over the needs of children to move around their neighbourhoods without
having to ask an adult to escort them (Rosenbaum 1993).
2.2.6 Traffic congestion
Traffic congestion in Australia has both health and economic costs. The current economic
costs of congestion in Australian capital cities are estimated to be $9.4 billion per year,
including $110 million in Canberra (Bureau of Transport and Regional Economics 2007).
Traffic congestion, car space requirements and costs are a major concern for a number of
school communities. Data for the ACT are not available, but in 1999, children being driven to
school accounted for about 17% of all trips by all people in the Melbourne Statistical
Division during the morning peak period between 8.30 and 9 am. Additionally, 39% of car
trips to school were home-school-home trips (ie not part of linked trips from home to school
to other destinations) (Morris et al nd).
Preventing traffic congestion and avoiding the necessity to provide extensive car-parking
facilities at schools have been major factors in the promotion of cycling to school in the
Netherlands (Ministry of Transport Public Works and Water Management 2009). Rose
(1999) noted in an evaluation of the Safe Routes to School program that concerns about
traffic congestion and car-parking at schools in Australia can be a major motivation for
implementing active school travel programs.
In summary, this section briefly reviewed the multiple health and social benefits of active
transport and reduced car use. Active transport constitutes an appropriate form of MVPA, in
23

many respects similar to the more traditional and widely recognized LTPA. Active transport
also has a number of co-benefits not generally associated with LTPA. These have been
described briefly above, and are summarised in Table 2.
Table 2: Comparison of benefits of active transport and leisure-time physical activity
Sufficient to achieve a health
benefit:
� Intensity
� Frequency
� Duration
Participation from priority
groups for physical activity
promotion in Australia
(hence social equity benefits)
� Adolescent girls
� Women
� Older adults
� Disadvantaged
groups
Addresses key barriers to
physical activity:
� Lack of time
� People believe they
are ‘not sporty’
� Cost
� Convenience
Co-benefits:
� IQ and educational
attainment
� Traffic congestion
� Environmental
sustainability
� Community liveability
� Children’s
independent mobility
Characteristics and benefits
of active travel
(AT)
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
�
Characteristics and benefits
of leisure-time physical
activity (LTPA)
�
�
�
These population groups are
less likely to participate in
LTPA
These barriers are less likely
to be addressed through
LTPA
While the benefits of active transport are considerable, there are also associated health
risks such as injury and exposure to air pollution. These health risks are briefly reviewed in
section 3.
�
24

3 Health risks associated with active transport to school
3.1 Traffic injuries
Active transport also carries a risk of injury in common with other forms of physical activity
such as sport and play. Pedestrian and cyclist injuries are often compared with risk of injury
as a car passenger since walking and cycling are alternative forms of transport. A
comparative analysis of 30 OECD countries found highly variable traffic crash fatality rates
for young people aged 0-16 years. Fatality rates varied by country, travel mode (walking,
cycling, car passenger), measures of traffic exposure (fatalities per population, number of
trips, or distance travelled), road safety policies and a range of socio-demographic factors
(Christie et al 2004; Christie et al 2007).
Absolute risk of fatality is low for all modes of travel in most OECD countries. For example,
Australia has:
� 1.69 child car passenger fatalities per 100,000 child population (ranked 21st 20 out of
26 OECD countries).
� 0.86 child pedestrian fatalities per 100,000 child population (ranked 13 th ).
� 0.39 child cyclists fatalities per 100,000 child population (ranked 13 th ).
An Australian child is therefore almost twice as likely to be killed as a car passenger than as
a pedestrian, and more than four times as likely to be killed as a car passenger than as a
cyclist (Christie et al, 2004).
While these absolute levels of risk are comparatively low, relative risks based on traffic
exposure (ie relative fatality rates per trip or per kilometre travelled) result in a different
pattern of risks by travel mode. Exposure-based relative risks are generally higher for
pedestrians and cyclists than for car passengers (about 4-10 times), but with large variations
between countries. Even in the current traffic environments in US and NZ 21 , one fatality
occurs for about 10 million km walked or cycled, decreasing to one for about 100 million in
the high active travel countries (Christie et al, 2004).
There is little evidence of a steady gradation in pedestrian and cyclist fatality rates across
countries (Christie et al 2004). Rather, there is a clustering effect with Sweden, the
Netherlands, Finland, Germany and Denmark classified as the ‘top performers’ for
pedestrian safety. These countries have a strong commitment to fostering high levels of safe
walking and cycling, and most have implemented a comprehensive package of integrated
traffic safety measures including:
� A strong approach to infrastructure measures for pedestrian safety.
20 Japan is ranked first (i.e. safest), with a fatality rate of 0.37 per 100,000 child population; with Turkey ranked
26 th (4.03 per 100,000). Australia, the US and NZ have among the highest fatality rates for child car passengers
(21st, 23rd and 24 th respectively) due in part to the distance travelled as a car passenger (Christie et al, 2004).
21 Australian data are not available.
25

� Compulsory road safety education for children aged 6-9 years.
� Conducting national road safety campaigns once a year or more (most countries
conduct regional publicity).
� Speed reduction measures including environmental modification, 30kph speed
limits, crossings with signals in most areas and very low speed limits outside schools.
� Legislation that assumes driver responsibility in an accident involving a child
pedestrian.
� Commissioned research on child pedestrian safety.
� Support for a range of child pedestrian safety initiatives.
The clustering effect (of countries performing well and less well) was even more marked for
child cyclist safety. Most of the top performing countries implemented a comprehensive
package of child cyclist safety measures (in addition to those listed above for child
pedestrians) including:
� Providing high levels of cycling infrastructure.
� Promotion of child cyclist road safety education and training (often compulsory).
� National and regional child bicycle safety campaigns.
There is widespread recognition across OECD countries that the health and social benefits of
active travel substantially outweigh the risks (Christie et al 2004). Consequently, rather than
reducing children’s exposure to traffic by discouraging walking and cycling, most OECD
countries have policies aimed at promoting active travel and making it safer. There is
variation, however, in commitment to active travel policies and implementation of the
safety measures that simultaneously reduce risk and promote active travel.
As well as implementing policies that have been shown to increase children’s active travel
and make it safer, additional improvements in pedestrian and cyclist child injury rates are
likely to result from a modal shift from car use to active travel. A recent modelling of the
‘safety in numbers’ effect for pedestrians and cyclists found that if a substantial share of
trips by motorised transport is transferred to walking or cycling, the total number of road
traffic crashes (including multi-vehicle and single-vehicle car crashes, as well as pedestriancar
and cyclist-car crashes) is reduced (Elvik 2009). More commonly, rates of pedestrian,
cyclist and overall road traffic injuries are observed to decline as active travel mode share
increases (Pucher and Buehler 2008; Litman and Doherty 2009).
3.2 Exposure to air pollutants
Motor vehicles emit a variety of air pollutants that are known to be associated with adverse
health effects. Consistent estimates of exposure to air pollution for different modes of
transport are not currently available, though it appears that exposure to air pollutants for
commuters in motor vehicles is considerably higher than ambient urban concentrations.
Pedestrians and cyclists may experience lower exposure than car occupants, but higher
26

espiration rates can result in cyclists experiencing greater inhaled quantities of some
pollutants than car passengers (Panis et al 2010).
This is a complex area with study findings varying for different pollutants, locations, weather
conditions, vehicle type, driving style and study methods (Panis et al 2010). What is certain
is reduced motor vehicle use will reduce the health risks of air pollution for all people in
urban areas. Choosing low traffic cycling routes can also reduce cyclists’ exposure to air
pollution, especially particulate matter, which is emitted in higher concentrations by dieselfuelled
vehicles such as buses and trucks.
A recent assessment of the impact on all-cause mortality of 500,000 people aged 18-64
years shifting from car to bicycle for short trips on a daily basis in the Netherlands found the
beneficial effects of increased physical activity are substantially larger (3 – 14 months
gained) than the potential mortality effect of increased inhaled air pollution (0.8 – 40 days
lost) and the increase in traffic crashes (5 – 9 days lost). The authors noted the benefits to
the population as a whole are even larger due to small reductions in air pollution,
greenhouse gas emissions and traffic crashes (deHartog et al 2010).
The substantial reductions in all-cause mortality associated with active transport reported
by Andersen et al (2000) in Denmark, and Matthews et al (2007) in China, indicate the
health benefits of commuter cycling (for adults) outweigh the health risks.
4 Rates of active travel to school in Australia and the ACT
4.1 Active travel to school in Australia and internationally
There is no current data available for children’s modes of travel to school and other
destinations in Australia. The Australian Bureau of Statistics conducted the last
comprehensive national survey in 1974. Age- and gender-specific data were not reported,
and neither were walking and cycling trip distances and/or travel times for young people’s
trips to school and other destinations. Information on children’s walking and cycling trip
distances and/or times are available from household travel surveys conducted in some
Australian cities and regions. These data, from large population centres in Australia, are
likely to be indicative of Australian national data.
The available information indicates that children’s rates of active travel to school and other
destinations in Australia are low and declining in contrast to several European and Asian
countries. International comparative data is summarised in Table 3. The increased
international variation in cycling and walking rates in relation to trip distance is discussed in
Section 5.
27

Table 3: Rates of walking and cycling to school (% students)
Location Participants Walk (%) Bike (%)
Walk + Bike
(%)
Victoria,
Australia
3,000; 5-12 y 23 4 27
US (2009) 14,553; 5-18 y 12 1 13
Canada (2001) 15
Great Britain,
2006 National
Travel Survey
5-16 y 46 2 48
The
Primary
37 49 86
Netherlands students
Germany 22 Up to 18 y Female: 37 Female: 18 Female: 55
Male: 37 Male: 21 Male: 58
Denmark (10
municipalities)
(1998-2000)
11-15 y 22 49 71
Izegem, 120, probability Urban: 13 Urban: 66 Urban: 79
Belgium sample, 12-19 y Suburban: 2 Suburban: 79 Suburban: 81
Portugal 450, 12-18 y 23
Russia 4-11 y 59
Jiangsu
431 males,
Male: 25 Male: 66 Male: 91
Province, China 393 females
12-14 y
Female: 21 Female: 63 Female: 84
(Note: data are indicative only, as measures of walking and cycling varied between studies)
(Sources: Sirard and Slater 2008; [UK] Department for Transport 2008; [Dutch] Ministry of Transport,
Public Works and Water Management 2007; Department of Human Services 2007)
4.2 Active travel to school in the ACT
4.2.1 Children’s overall physical activity levels
The 2006 and 2009 ACT Physical Activity and Nutrition Surveys (ACTPANS) for Year 6
students provide data on children’s general physical activity levels including in and outside
of school, involvement in organised sport, active transport and levels of sedentary activity
(ACT Health 2007).
The 2006 survey found that 19% of children met the Australian Government physical activity
guidelines of moderate to vigorous physical activity for at least 60 minutes every day. Boys
(24.9%) were significantly more likely than girls (13.6%) to report this level of activity. The
mean number of days that children reported being moderately to vigorously physically
active for at least 60 minutes a day was 4.8 days per week for boys and 4.3 days for girls.
22 Main travel mode for all trips (1997).
28

4.2.2 Children’s participation in active transport
Information about children’s modes of travel to education in the ACT is available from three
data sources. ABS data are available for 1970 and 1974, household travel survey data are
available for 1997 and Year 6 students’ modes of travel to and from school are available
from the 2006 and 2009 ACT Physical Activity and Nutrition Surveys (ACTPANS). There is
considerable variation in the data collection methods used in these various surveys, and in
the ways the data are analysed and reported, so care needs to be taken in examining trends
in students’ modes of travel to school/education over time. However, the changes in their
travel modes over time are large, and the findings are consistent with other Australian data
which is likely to provide an adequate indication of trends in travel to school/education in
the ACT.
In 1970, more students travelled to school or university in the ACT by bicycle (13.1%) or
walking (46.8%) than by car (12.1%) 23 (Australian Bureau of Statistics 1975). By 1997 only
29.7% of students walked (22.2%) or cycled (7.5%) to full-time education (Brown and Nairn
1997). The decline over time, and current rates of active travel to school, are similar to
those in Victoria (27% of students aged 5-12 years), though somewhat higher than in the
Greater Sydney Metropolitan Area (22% of primary school students) (Garrard 2010).
In 2006, 30.5% of Year 6 students 24 walked or cycled to school 25 (Population Health
Research Centre ACT Health 2007). Care needs to taken in comparing this rate of active
travel to school with the 1997 figure (29.7%) due to differences in the study population (the
1997 data includes travel to school and higher education), and the measure of active
transport (five times in a typical week, compared with one day’s travel). Preliminary analysis
of 2009 data indicates a statistically significant decline between 2006 and 2009 (30.5% and
24.3% respectively) in the proportion of Year 6 students walking or cycling to school every
day (ACT Health, preliminary analysis of 2009 ACTPANS data).
5 Potential for mode shift to active travel to school: the role of trip distance
One of the most consistently reported reasons for driving children to school in Australia is
the trip distance is too far for walking or cycling (Garrard et al, 2009). This section presents
data which indicates substantial potential for increasing active travel to school in terms of
feasible walking and cycling distances.
The following discussion is based on the most recent, comparable data for mode share of
trips to and from education by trip distance. It was collected by the ABS for travel to and
from education in Victoria in 1984 and 1994. Victorian data is used because the ABS ceased
collection of national data for all modes of travel in 1984, and Victorian data in 1994.
23 Full-time students aged 5 years and over.
24 These data are for grade 6 students only, but levels of active travel among young people in Australia show
little variation between grades 4 and 8.
25 Five times in a typical week.
29

Figures 4 and 5 show mode share changes in travel to school over time in Victoria (1984 to
1994) for trips less than one kilometre (Figure 4), and trips between one kilometre and less
than 5 km (Figure 5). This data shows substantial decreases in active travel between 1984
and 1994 for the relatively short distances that are considered feasible for walking and
cycling.
Figure 4: Mode of travel to school (1984) or education (1994) for trips less than one
kilometre, respondents’ usual mode of travel (%), Victoria
Source: Australian Bureau of Statistics (1995) and Australian Bureau of Statistics Victorian
Office (1985)
Figure 5: Mode of travel to school (1984) or education (1994) for trips between 1
kilometre and less than 5 km, respondents’ usual mode of travel (%), Victoria
(Source: Australian Bureau of Statistics 1995, Australian Bureau of Statistics 1985)
30

International comparative data show that relatively short trips that are often made by car in
Australia are more often walked or cycled in other countries. Figure 6 shows that car trips
were the predominant mode of travel to education for all distances between 500 metres
and 10 km in 1994 in Victoria. In contrast, data from 10 municipalities in Denmark show that
walking and cycling are the predominant modes of travel to school for distances up to 3 km,
and cycling rates remain substantial for all trip distances up to and beyond 8 km (Figure 7).
Figure 6: Main method of travel to an educational institution (primary, secondary, higher
education) by distance travelled, Victoria, 1994 26
(Source: ABS 1995)
Figure 7: Mode share of all trips to/from school by distance, 10-15 year olds, 10 Danish
municipalities, 1998-2000
(Source: Jensen and Hummer 2003)
26 The most recent data available on school travel mode by distance at national or state level.
31

In summary, compact urban form facilitates short walking trips (Table 1), while decent
system-wide cycling conditions (cycling infrastructure, traffic calming and car restrictions)
are required to support cycling to school as trip distances increase (the Netherlands,
Germany, Denmark) (Garrard, 2009). In countries with decent provision for cycling, young
people cycle relatively long distances to school including through suburbs similar to those
surrounding Australian cities (van Dyck et al 2009). In contrast, car trips largely replace
walking trips for trip distances greater than about 1 km in Australia, the UK, the US and
Canada.
6 Effectiveness of interventions aimed at increasing children’s rates of active
travel to school
Active school travel programs are relatively new initiatives compared to programs
promoting leisure-time sport and exercise for children. The evidence-base for their
effectiveness is limited, with the findings of a small number of reviews summarised in the
following section.
6.1 Evidence reviews
Active school travel programs typically include some combination of the following measures
as outlined by Möser and Bamberg (2008):
� Special walking or cycling promotion days.
� A program of pedestrian and cycle training for children.
� Bicycle parking.
� Activities as part of the curriculum to promote the benefits of sustainable transport.
� Physical changes to the streets around the school such as 40 km/h limits, traffic
calming, pedestrian crossings and bicycle lanes.
� Developing a school travel policy and/or home-school agreement.
A number of recent systematic and narrative reviews that include school programs aimed at
increasing active travel to school and/or reducing car travel have been published (Ogilvie et
al 2007; Möser and Bamberg 2008; Hosking et al 2010; Pucher et al 2010; Yang et al 2010;
Chillon et al 2011). These reviews indicate that not all programs have achieved small-tomoderate
increases in rates of active travel to school. Variable program impacts occur both
between programs and for individual schools within multi-site programs.
Much of this evaluation literature is relatively recent, and there has been little systematic
assessment of the reasons for variable program impacts. However, based on limited
process/implementation evaluation data to date, the determinants of success are likely to
include factors associated with schools and their social, cultural and built environments,
program type and quality of program implementation. Evaluation designs and methods also
impact on evaluation findings.
32

6.2 Recent evaluations of active school travel interventions
6.2.1 Australia
An evaluation involving five out of 15 primary schools in suburban Sydney that participated
in the NSW TravelSmart program reported active travel to school (defined as walking,
cycling or public transport) increased over the program period in three out of the five
schools 27 (Fry 2008). The Central Sydney Walk to School Research Program, which
comprised a randomised controlled trial involving 24 government primary schools in inner
suburban Sydney, reported inconsistent evidence of an impact on students’ walking trips to
and from school. Parent-reported data showed an increase in students’ walking trips, while
student-reported data showed no significant changes (Wen et al 2008).
Walking School Bus
Walking School Bus (WSB) programs have been conducted in a number of states and
territories in Australia. One of the largest WSB programs was conducted in Melbourne by
VicHealth with $4.5 million committed to councils from 2001 to 2011 to develop and
implement the WSB system. VicHealth, in partnership with councils, provided funds to cover
some or all of the costs of employing a WSB coordinator, promoting the program, recruiting
schools, engaging and training volunteers and auditing/establishing WSB routes.
The program involves children walking in a group with an adult driver/supervisor (usually
parents of school students) at the front, and an adult conductor/supervisor at the rear. The
bus travels along a set route picking up additional passengers along the way at designated
bus stops. WSB project officers (appointed by each council) were responsible for recruiting
schools, providing training and other support for the volunteer walkers and liaising with
agencies such as VicRoads and Victoria Police.
WSB ‘Snapshot data’ for November 2007 showed 51 council areas were involved in
delivering the WSB program. They engaged 141 schools that operated 255 WSB routes, with
487 buses and 4,507 children walking to school as a direct result of the WSB program. These
children were supported by at least 974 volunteers. 28
Evaluations of Walking School Bus programs (including economic assessments) indicate it is
resource-intensive and of limited cost-effectiveness when implemented as a stand-alone
program (Ker 2009), or when assessed solely in terms of obesity prevention benefits
(Moodie et al 2009). VicHealth no longer funds the WSB in Victoria. It is now conducting the
Streets Ahead program aimed at increasing children’s independent mobility (including active
travel to school) within selected communities.
27 Aggregated findings across the five schools were not included in the report.
28 http://www.vichealth.vic.gov.au/wsb
33

Streets Ahead
VicHealth’s Streets Ahead program builds on the knowledge base from the Walking School
Bus to develop more comprehensive and flexible children’s independent mobility
demonstration projects in six communities in metropolitan Melbourne and regional Victoria.
The program aims to increase physical activity in children aged 4 to 12 years through active
transport. VicHealth committed $1.7 million over three years from July 2008 to June 2011
to:
� Establish community action groups that help identify barriers to children’s active
transport and independent mobility, and develop strategies to overcome them.
� Increase the rate of children walking and cycling to school, and for older children to
do so independently.
� Increase the rate of children using active transport to move around their local
neighbourhoods, be out in the parks and other public places, and for older children
to do so independently.
The program provides funding to six local councils to employ a full-time coordinator to
enable communities to create supportive environments that enhance children’s active
transport and independent mobility in all aspects of their community life including to and
from school. 29
Ride2School program (Victoria)
An evaluation of the first two years (mid-2006 to mid-2008) of the Ride2School program in
Victoria found:
� An increase in active travel to school in an inner Melbourne suburb with a
committed school, located in a supportive environment and a relatively intensive
intervention program.
� Mixed evidence of an increase in active travel to school across 13 primary schools in
rural and metropolitan Melbourne following a less intensive intervention program.
� An increase in active travel to school on ‘special event’ days (eg annual Ride2School
Day, monthly Hands Up! surveys).
� An increase in cycling to school following installation of bike storage facilities in 36
schools (Garrard et al 2009).
Active School Travel Program (Brisbane)
The Brisbane Active School Travel (AST) program, delivered by the Brisbane City Council,
commenced in its current format in 2004. The program was conducted in eight schools in
the first year of operation; 10 schools in 2005 and 2006; 13 schools in 2007 and 2008; and a
total of 21 schools in 2009 including one High School. Each year the cohort of participating
schools includes some existing and some new schools.
29 http://www.vichealth.vic.gov.au/streetsahead
34

The AST program aims to achieve a target of 10% reduction in sole family car trips to school.
Within the AST program, Council assists each school to develop a School Travel Plan (STP)
which is a framework to facilitate behaviour change towards active and sustainable
transport modes. The STP is supported by a number of initiatives that reinforce the aim of
the project including:
� Bike Skills Training.
� Walking Wheeling Wednesday.
� Walking School Buses.
� Park and Stride.
� Carpooling.
� Road Safety Education.
Active School Travel Project Officers work with school communities for an initial intensive
year to integrate these initiatives into a sustainable School Travel Plan which is incorporated
into the school’s operational plan. From 2009 the AST program included Council Officer
support for schools that actively engaged with Council to continue AST activities. AST has
been developed into a three-year program with varying levels of support given to schools as
the program becomes more sustainable.
School staff conducts pre and post ‘Hands Up!’ surveys of student’s travel modes to and
from school over five consecutive day periods each November. There was a reported 24.8%
increase in active travel mode share to school in 2008, and an 18.1% increase in active travel
mode share from school across the 13 primary schools that participated in the 2008 AST
program. Walking trips to school increased by 19.1% (from 19.0% to 38.1%), and cycling
trips by 3.1% (from 3.9% to 7.0%) (Brisbane City Council 2009).
It is not known what proportion of student’s school trips are linked trips (drive-walk or
drive-cycle). Partway active trips are encouraged through the ‘Park and Stride’ component
of the program, and students who walked or cycled partway may have answered as either
walk/cycle or car. It is likely that the major or last part of the journey would be recorded,
but this was not specified in the data collection. In terms of the likely active commute
distance for linked trips, the program recommends to parents that 500 metres is the
minimum (as detailed in the school's AST Travel Map where a 500 metre ring is drawn
around the school), although adherence rates have not been assessed.
The 2009 AST evaluation showed five of the original 13 schools from 2007, and seven out of
13 schools from the 2008, were still engaged with the AST program. The extent schools
which no longer participate in annual data collection continue to support active travel to
school is unknown, or whether they continue to maintain or further increase initial postprogram
increases in active travel to school.
35

6.2.2 International AST programs
Auckland School Travel Plans
The Auckland Regional Transport Authority’s 2007 School Travel Plan evaluation, based on
data collected from 35,153 students across 68 primary and secondary schools in New
Zealand, reported a reduction in travel by ‘family car‘ of 3.4% (Sullivan and Percy 2008).
Changes in the use of active and public transport ranged from +14.9% to -15.6%, with twothirds
of schools experiencing increases and one-third decreases. Overall, the Auckland
School Travel program has achieved:
� A decrease of 3.4 percentage points (approx. 7% relative) in car use.
� 2.4 percentage points (approx. 7% relative) increase in active travel (walking and
cycling).
� 1.0 percentage point (approx. 9% relative) increase in public transport use (Hinkson
et al 2008).
While there are some unknown variables, a recent assessment of the Auckland Regional
School Travel Plan Program (Hinckson et al 2008, p. 16) found that:
…schools that have participated for one or two years average a 3.0% increase in active and
public transport. This rises to 4.0% in schools with a School Travel Plan for 3 years. These
patterns suggest that the maximum benefits may require three years of implementation.
Whether or not subsequent years would result in further improvements requires further
investigation.
USA Safe Routes to School
The Safe Routes to Schools program operates in over 7,622 schools (as of mid 2010) across
the USA. A nation-wide ‘Hands Up!’ survey of over 130,000 parents and over a million
students to gather baseline data regarding their travel behaviour and attitudes to school
transport found travel behaviour was strongly influenced by the distance between home
and school. A significant proportion of very short trips were completed by motor vehicle,
with parents whose children live within 800m of school but do not allow them to walk or
cycle citing safety as the primary issue.
Sustrans UK
Results from Sustrans’ flagship ‘Tackling the School Run’ program in 2007-08 indicated a
doubling (on average) of the use of cycling and walking routes around schools where new
paths were constructed or upgraded. As estimated 135,690 more cycling and walking trips
to school were made throughout Scotland, and approximately 30,929 pupils across Scotland
now have access to safer walking and cycling routes to school.
6.3 Summary of the impacts of active transport initiatives in schools
Variable program impacts occur both between programs and for individual schools within
multi-site programs. Much of the evaluation literature is relatively recent with little
systematic assessment of the reasons for variable program impacts. However, based on
36

limited process/implementation evaluation data to date, the determinants of success are
likely to include factors associated with schools and their social, cultural and built
environments, program type and quality of program implementation. Evaluation designs
and methods also impact on evaluation findings. Programs have generally been more
successful in increasing walking than cycling in countries such as Australia, the UK and the
USA. This discrepancy needs to be addressed to reduce car use and increase active transport
for the considerable number of trip distances to school greater than 1 km.
6.4 Aggregate level change
Active school travel programs often lead to increased levels of active travel to school in
participating program schools, but there is little evidence of an overall mode shift to active
travel in countries like Australia with low rates of active travel.
A recent analysis of school travel data found few statistically significant changes in young
people’s modes of travel to and from school in Victoria between 2006 and 2009, and in the
greater Sydney Metropolitan area between 2005 and 2008 (Garrard 2010).
Similar findings of increased cycling in program schools, but little community-wide increase,
have been reported for Cycling England’s ‘Cycling Demonstration Towns’ project. Pooled
data from Hands Up surveys (conducted in 2006-07 and 2007-08) of students in Bike It
schools, which received the intensive support of a ‘Bike It’ officer, showed an increase in the
proportion of students cycling to school every day or ‘once or twice a week’ of 20.4% (from
8.7% to 29.1%). School census data (all schools, students up to 15 years old, 2006-07 to
2007-08) reported an increase of 0.1% (1.5% to 1.6%) in the number of students for whom
cycling is the usual mode of travel to school (Sloman et al 2009).
Similar findings have been reported in Scotland. A survey in September 2009 of about
415,000 children (approximately 59% of all pupils in Scotland), conducted by ‘Hands-Up!’
Scotland in partnership with Sustrans and local authority School Travel Coordinators, found
a 1.3% drop in the number of children walking to school and a 0.5% decrease in the number
of children cycling on the same journey. However, the number of children who travelled to
school by car increased by just over one percent. These aggregate data disguise
improvements in some localities, and 13 of the 31 local authorities that took part in the
survey reported an increase in some modes of active travel.
In contrast to Australia, England and Scotland, high area-level rates of active travel to school
have been achieved in countries such as Denmark and the Netherlands. Analysis of school
travel mode by trip distance demonstrates that these differences in school travel mode are
not primarily due to greater travel distances in Australia and the UK (see Section 5).
These findings suggest that achieving the multiple and substantial benefits of active travel at
the population level requires implementing behaviour change programs with demonstrated
37

efficacy with commitment and wide program reach, which is supported by environmental
and policy changes that help to make active travel choices easy choices.
7 Understanding the influences on active travel to school
The factors that influence children’s modes of travel to school are complex, but some useful
models have been developed that aid understanding and guide practice. Two models are
described: (i) a social-ecological model of active transport derived from models of children’s
physical activity behaviour; and (ii) a perceived benefits/barriers model derived from the
community-based social marketing (CBSM) approach for fostering sustainable behaviour
(McKenzie-Mohr and Smith 1999).
7.1 Social-ecological model of active school travel
The social-ecological model shown in Figure 8 provides a framework for summarising the
multi-faceted influences on children’s school travel behaviour. While the model appears
relatively straightforward, in reality the factors are complex. For example, many of the
environmental influences on active travel have both a perceptual and an objective element
(eg ’too far to walk/cycle‘). The multiple intra-individual factors (eg knowledge, beliefs,
attitudes and preferences) apply to both young people and parents, as both are involved in
the choice of school travel modes. As in all ecological models of behaviour, component
factors are mutually interactive. For example, the built environment both shapes and is
shaped by the social/cultural environment.
Social/cultural
environment
Physical environment
(natural and built)
Policy/regulatory
environment
Intra-individual
factors
Travel behaviour
Figure 8: Influences on children’s active travel behaviour
(Adapted from Gebel et al 2005)
It is well established that most children prefer to walk or cycle to school yet parental
preferences often over-ride those of children (Garrard et al 2009). The main reasons
38

children give for preferring to walk or cycle to school are enjoyment, health and exercise,
socialising with friends and quick travel time. The main reasons for parents preferring to
drive their children to school centre on the convenience, speed, comfort and safety of car
travel (Garrard et al 2009).
These issues have both a ‘perceptual’ and ‘actual’ element, and are strongly influenced by
social/cultural values and behavioural norms. For example, ‘too far to walk/cycle’ varies
between countries and within Australia over time. Concerns about traffic and child safety
(as reflected in the levels of independent mobility that parents permit their children) also
vary between countries and over time in Australia. Traffic safety has improved over time in
Australia, and there appears to be no evidence of an increase over time in abduction,
robbery, assault and homicide committed against children by strangers in Australia (Zubrick
et al 2010).
Research in the field of risk assessment/communication can assist in understanding, and
perhaps addressing, the perceived risks of children’s independent travel. Risk perceptions
are often based on emotional responses to situations rather than rational analyses (Slovic et
al 2004). In turn, emotional responses are shaped by a range of psychological and social
processes.
Risk perception research has identified a number of ‘biases’ that contribute to misjudging of
risk in general (Slovic et al 2004), and may foster inordinate parental ‘fear of independent
mobility among children’. In particular, familiarity bias and control bias may reduce the
perceived risks associated with car travel and increase the perceived risks for active
transport. For example, familiarity bias can arise in low-cycling countries because driving is a
familiar activity but cycling for transport is relatively unusual. We adjust to the everyday
risks of driving, but are relatively more fearful of the ‘unknowns’ of cycling for transport.
Control bias arises when cyclists and motor vehicles share road space forcing parents to
largely surrender control for the safety of their children to the children themselves and to
unknown car drivers. Although little research has been conducted, ‘trust in others’ might be
an important determinant of children’s independent mobility (Garrard 2009; Zubrick et al
2010).
The Netherlands in the 1970s, the risks posed by motor vehicles to child cyclists and
pedestrians were a major factor for the introduction of traffic safety measures that
prioritised cyclist and pedestrian safety over motor vehicle mobility. Examples include 30
km/hr speed limits in most urban areas, and the legal responsibility of car drivers to avoid
collisions with cyclists. The Dutch approach is: “Cyclists are not dangerous; car drivers are:
so car drivers should take the responsibility for avoiding collisions with cyclists” (Ministry of
Transport Public Works and Water Management 2009).
These measures have contributed to a cycling environment that both is, and is perceived to
be, safe and pleasant, and where parents feel comfortable allowing their children to move
39

about independently. In the Netherlands, measures are taken to increase the perceived
safety and desirability of cycling, as well as the actual safety and convenience. In contrast,
motor vehicle mobility is prioritised in Australia where the road environment feels (and to
some extent is) unsafe for walking and cycling. Parents have responded by driving their
children for increasingly short distances that are feasible to walk or cycle.
Another constraint on active travel to school is the trend in car-oriented countries to
effectively blame parents for permitting their children to participate in ‘risk-taking
behaviour’, such as travelling independently to school, should the child be injured in a
collision with a car (Jacobsen et al 2009; Skenazy 2009). Concerns about social blame
and personal guilt are less of a constraint in high active travel countries because (a)
the responsibility for avoiding collisions with child pedestrians and cyclists clearly
rests with car drivers (and collisions are less likely to occur); and (b) independent
travel to school is not deemed to be ‘risk-taking behaviour’ when ‘everybody does it’.
Similarly, travelling long distances with children in cars (which contributes to
Australia having a relatively high rate of child road traffic fatalities per 100,000
children – see Section 3.1) is not viewed as ‘risk-taking behaviour’ in Australia
(provided they are appropriately seated), partly because it is common practice.
The natural and built environments and policy/regulatory environments (see Figure
8) also influence children’s travel behaviour both directly and interactively via social,
cultural and individual factors. More detailed reviews of these influences on
children’s active travel can be found in Garrard (2009), Pont et al (2009) and Davison
et al (2008).
7.2 Perceived benefits/barriers model of active school travel
The community-based social marketing (CBSM) approach developed by McKenzie-Mohr and
Smith (1999) involves fostering voluntary behaviour change by identifying and addressing
the perceived benefits and barriers to the targeted behaviour (active travel to school) and
the competing behaviour (driving to school).This frequently involves assisting people to do
the things are they already predisposed to do, but are constrained by barriers to action. For
example, about two-thirds of parents of grades 4-6 students in 13 primary schools in
Victoria stated that regular walking or cycling to school was a possibility for their child, but
less than half of students’ trips were by walking and cycling (Garrard et al 2009). The aim of
the CBSM approach is to turn the possibility into reality by addressing the real and perceived
barriers to action. These barriers (figure 8) can be personal, environmental, social/cultural
or policy/regulatory which can all impact on active travel behaviour.
The CBSM approach also highlights the importance of recognising that travel mode choices
involve choosing between multiple transportation options (principally driving, walking or
cycling), which have their own set of perceived and actual benefits and barriers. This
distinguishes promoting active travel to school for children and adolescents from other
40

forms of physical activity promotion. Active travel to school is a travel choice as well as a
physical activity choice that involves both parents and children.
Key elements of the CBSM model include using a range of research and consultation
processes with program stakeholders and target groups to identify the perceived benefits
and barriers to the ‘new behaviour’ (active travel to school) and the ‘alternative behaviour’
(car travel to school). This information contributes to the development of strategies aimed
at increasing the perceived benefits and reducing the perceived barriers of active travel to
school, while simultaneously reducing the perceived benefits of car travel and increasing the
perceived barriers to car travel. Identification of benefits and barriers should be based on
evidence from the research and evaluation literature, and from qualitative and quantitative
research conducted with the program’s target group(s). Similarly, choice of strategies is
both evidence-based and locally adapted. Table 4 illustrates the benefit/barrier matrix with
examples of possible perceived benefits and barriers for active and inactive travel to school.
Table 4: Perceived benefits and barriers of active and inactive modes of travel to school
Perceived benefits
Perceived barriers
Target behaviour (active
travel to school)
Competing behaviour
(travelling to school by
car)
Improves health Saves time
Poor access to direct, safe
walking/cycling routes
Difficult to park car at
school
The CBSM model stresses the pattern of perceived benefits and barriers will differ for
population subgroups, and for different active travel modes. For example, boys may have
different perceived benefits and barriers from girls, the benefits and barriers are likely to
differ for parents in paid employment compared with those who are not while walking to
school might have different barriers to cycling. These differences require a degree of
strategic ‘market segmentation’.
The CBSM model also recommends addressing individual component ‘steps’ in the desired
overall behaviour. Parents in 13 primary schools in Victoria identified getting up earlier,
being more organised and planning for walking or cycling to school as steps in the process of
changing from car travel to active travel. Cycling to school also requires preparation in terms
of bicycle maintenance and appropriate school clothes and bags. Other steps might include
organising to travel with a school friend, familiarity with a safe route to school, ensuring
students have the road skills to walk or cycle and establishing an informal network of adult
neighbours or friends to share accompanying children on the trip to school. Deciding which
behaviours to promote by what means depends on the potential to bring about the desired
41

change and to what extent resources are available to overcome identified barriers and
enhance perceived benefits (McKenzie-Mohr and Smith 1999).
The promotion of active travel to school also includes reducing the perceived benefits and
increasing the barriers to car travel. Reduced speed limits in school zones, car parking
restrictions near schools and giving pedestrians and cyclists priority are examples of
increasing barriers to car travel used successfully overseas (Pucher and Buehler 2008). There
is also potential to change drivers’ perceptions of the speed and cost of car travel, as
research demonstrates that people consistently underestimate the cost and overestimate
the speed of car travel (Tranter 2004; Vanderbilt 2008; Litman and Doherty 2009).
8 Future directions/innovations for promoting active travel for children in
Australia and the ACT
The multiple health and social benefits of active travel for children have led many countries,
cities and communities to implement policies and programs aimed at increasing children’s
rates of active transport to school and other neighbourhood destinations.
Two broad areas of evidence can be used to inform active transport interventions: (a)
program evaluation findings (eg evaluation of TravelSmart-type programs in community or
school settings); and (b) policy evaluation (eg monitoring changes in transport mode share
in regions, cities, towns or communities that have implemented an integrated package of
measures aimed at increasing active travel and decreasing car use).
Program evaluation can provide information about what is effective in existing programs.
Policy evaluation provides guidance for establishing an ‘active transport place’ 30 where
children walk or cycle to school because active transport is established as a convenient, fast
and safe mode of transport for the whole community. Macro-level policy evaluation is less
precise than program evaluation in terms of quantifying the impacts of specific components
of a multi-component strategy, but it provides a better assessment of the reach,
effectiveness and sustainability of holistic efforts to achieve change at the societal level.
A review by Pucher et al (2010) of the effectiveness of interventions to increase cycling
incorporated both program evaluation findings (eg infrastructure measures, social
marketing programs) and policy evaluation findings (eg what packages of measures have
been implemented in cities and towns that have increased bicycle mode share of travel?).
The authors stated it is difficult to isolate the separate impacts of individual interventions
designed to promote cycling as they are expected to be interactive and synergistic. For
example, marketing programs are likely to be influenced by the extent and quality of the
bicycle network.
30 A ‘place’ can be a country, city, town or suburb.
42

Case studies provide an opportunity to examine the impacts of packages of mutually
supportive cycling promotion policies. The review by Pucher et al (2010) included case
studies of 14 cities and towns, which were diverse in terms of geography, size and preintervention
levels of transportation cycling,that have implemented a wide range of
measures to increase cycling and improve cycling safety. These measures typically included:
� Decent walking and cycling infrastructure.
� Transportation policies that address the needs of all road users and facilitate the
linking of active trips with public transport use.
� Policies and programs that improve the safety of pedestrians and cyclists.
� Programs that promote active transport.
� Disincentives for car use including fewer provisions for car use and parking, and
lower subsidies for car purchase, operation and parking.
These measures are consistent with those identified by Christie et al (2004; 2007) derived
from policy evaluation in 26 OECD countries which improved the safety of child pedestrians
and cyclists (see Section 3.1).
Overlapping findings from Pucher et al (2010) for cycling promotion, and Christie et al (2004;
2007) for child pedestrian and cyclist safety, highlight the well-established links between the
prevalence and safety of active transport – strategies that improve safety also improve
participation, and vice versa.
Carefully planned and well-implemented behaviour change programs are a necessary but
not sufficient condition for population-level change in school travel modes. The evidence
reviewed in this report indicates that in several countries and regions (England, Scotland,
Victoria, NSW and ACT), population levels of active travel to school have not changed
despite programs with impressive impacts in some schools and for special events (eg
walk/ride to school days).
Strategic planning and a systems approach are required to move towards the levels of active
travel to school that have been achieved in a number of other high-income countries.
Programs such as the Brisbane City Council Active School Travel provide a model for an
active school travel program, while cities and towns in countries such as Denmark,
Germany, the Netherlands and Japan provide models for implementing more broadly-based
policy packages.
Effective active transport policy models are not restricted to the high active travel countries
in Europe and Asia. The USA cities of Davis, California and Portland have achieved high levels
of active transport, including among children. In Davis, 43.4% of boys and 30% of girls cycle
to high school in stark contrast to the USA as a whole (Emond and Handy 2010).
Active travel choices can be easy choices, including within urban environments similar to the
low population density suburbs surrounding Australian cities (van Dyck et al 2009).
43

Differences in travel mode share over time (in Australia/Victoria) and geographically (among
OECD countries) broken down by trip distance indicate that transportation policies and
infrastructure are more important determinants of young people’s active travel than urban
form. Social norms of travel that shape perceptions of feasible walking and cycling
distances, personal and traffic safety and ‘responsible parenting’ are also important
(Thomson 2009). These factors are amenable to change in the short-term, in contrast to
longer-term developments aimed at creating more compact urban environments.
Data summarised in this report suggest the greatest potential for increasing rates of active
travel to school lies in encouraging more young people to walk up to about 1 km and cycle
up to about 5 km. With the right conditions, policies, education and encouragement, more
children would walk or cycle to school and other neighbourhood destinations.
Elements of a strategy to increase active travel to school that includes school-based
programs, together with area-wide and population-wide strategies for increasing active
travel in the wider community, could include:
� Setting goals and targets (eg an increase of 5% in the walking and cycling mode share
of travel to education in a 5-year period 31,32 ).
� Specifying components of the strategy (eg, incorporating the 4Es of Education,
Encouragement, Engineering and Enforcement).
� Well-defined ‘program logic’ (ie Are we doing the right things? Is the intervention
‘dose’ appropriate? Is the program reach adequate?).
� Identifing partners, responsibilities and resources (eg who is responsible for each
component?).
� Evaluation/monitoring (eg including measures of travel to school in school data
collection systems).
The key health promotion strategies of community participation, advocacy and intersectoral
partnerships will also be important in achieving these goals. Many sectors and
levels of government have a role to play in increasing children’s and adults’ use of healthy
and sustainable transport modes for the many short-to-medium trips that typify children’s
travel in urban areas.
31
This is approximately the rate at which walking and cycling to education have declined in the last 40 years in
Victoria.
32
The recent White House Task Force on Childhood Obesity Report to the President (Solving the problem of
childhood obesity) set a target of an increase in bike/walk trips to school in the USA of 6.5 percentage points by
2015.
44

9 Conclusions
Active transport for children can contribute to a range of health and social benefits, but
children’s active travel rates in Australia appear to be declining. This report demonstrates
that increasing levels of car use is not the inevitable by-product of low-density suburban
living in affluent countries, but the predictable outcome of transportation policies that
promote car use and (albeit unintentionally) constrain walking and cycling.
Changes can be achieved, at least in the short-term, through programs such as Safe Routes
to School, Walking School Bus, School Travel Planning and Walk/Ride to School events.
These initiatives need to be complemented by area-wide improvements that create
supportive environments for active travel. The experiences of overseas countries, cities and
municipalities provide a model for sustainable transport planning aimed at increasing active
travel to school in the ACT.
Implementing active travel initiatives, and assessing their effectiveness in participating
schools, is important, but key questions to also consider include (i) the program and
contextual factors that shape the effectiveness of interventions; (ii) the sustainability of
change; (iii) the reach of active travel initiatives; and (iv) the role of supportive communitywide
measures. Public health strategies in areas such as tobacco control, road safety and
child immunisation are successful because they have achieved measurable improvements at
the population level and not just in selected schools or communities. The much-cited
benefits of active travel will be realised when measurable change occurs at the population
level.
45

References
Åberg, MAI, Pedersen, NL, Torén, K, Svartengren, M, Bäckstrand, B, Johnsson, T, Cooper-Kuhn, CM,
Åberg, ND, Nilsson, M, Kuhn, HG (2009). Cardiovascular fitness is associated with cognition in
young adulthood. Proceedings of the National Academy of Sciences 106(49): 20906-209011.
Ainsworth, B, Haskell, W, Whitt, M, Irwin, M, Swartz, A, Strath, S, O'Brien, W, Bassett, D, Schmitz, K,
Emplaincourt, P, DRJRJacobs, Leon, A (2000). Compendium of physical activities: an update of
activity codes and MET intensities. Med Sci Sports Exerc 32(9 Suppl): S498-504.
Andersen, LB, Schnohr, P, Schroll, M, Hein, HO (2000). All-cause mortality associated with physical
activity during leisure time, work, sports, and cycling to work. Arch Intern Med 160(11): 1621-
1628.
Andersen, L, Lawlor, D, Cooper, A, Froberg, K, Anderssen, S (2009). Physical fitness in relation to
transport to school in adolescents: the Danish youth and sports study. Scandinavian Journal of
Medicine and Science in Sports 19(3): 406-411.
Appleyard, D, Lintell, M (1980). The environmental quality of city streets: the residents' viewpoint.
Journal of the American Institute of Planners 38: 84-101.
Australian Bureau of Statistics (1975). Journey to work and journey to school, August 1974.
Canberra, ABS.
Australian Bureau of Statistics (2007). Health of Children in Australia: A Snapshot, 2004-05, Cat No.
4829.0.55.001. Canberra, ABS.
Australian Bureau of Statistics (2009). National Health Survey: Summary of Results, 2007-08, Cat. No.
4364.0. Canberra, ABS.
Australian Bureau of Statistics (2009). Children's participation in cultural and leisure activities,
Australia, April 2009. Cat. No. 4901.0. Canberra, ABS.
Australian Bureau of Statistics (2010). Crime Victimisation, Australia, 2008-09 Canberra, ABS.
Badland, H, Oliver, M, Duncan, M, Schantz, P (2011). Measuring children's independent mobility:
comparing objective and self-report approaches. Children's Geographies 9(2): 263-71.
Booth, ML, Okely, AD, Denney-Wilson, E, Hardy, L, Yang, B, Dobbins, T (2006). NSW Schools Physical
Activity and Nutrition Survey (SPANS) 2004: Full Report. Sydney, NSW Department of Health.
Bosselmann, P, MacDonald, E (1999). Livable streets revisited. Journal of the American Planning
Association 65(2).
Brisbane City Council (2009). Active School Travel Program: 2008 summary evaluation report.
Brisbane, Brisbane City Council.
Brown, W, Nairn, R (1997). Report on the analysis of the Canberra/Queanbeyan Household Interview
Travel Survey - 1997. Canberra, ACT Government Department of Urban Services & Queanbeyan
City Council.
Bureau of Transport and Regional Economics (2005). Health impacts of transport emissions in
Australia: economic costs. Canberra, Department of Transport and Regional Services.
Bureau of Transport and Regional Economics (2007). Estimating urban traffic and congestion cost
trends for Australian cities, Working Paper 71. Canberrra, Department of Transport and Regional
Services.
Burke, M, Brown, AL (2007). Distances people walk for transport. Road & Transport Research 16(3).
Carver, A, Timperio, A, Crawford, D (2008). Playing it safe: The influence of neighbourhood safety on
children's physical activity--A review. Health & Place 14(2): 217-227.
Carver, A, Timperio, A, Crawford, D (2008a). Perceptions of Neighborhood Safety and Physical
Activity Among Youth: The CLAN Study. Journal of Physical Activity and Health 5(3): 430-44.
Chillon, P, Evenson, K, Vaughn, A, Ward, D (2011). A systematic review of interventions for
promoting active transportation to school. International Journal of Behavioural Nutrition and
Physical Activity 8(Feb 14): 10.
Christie, N, Cairns, S, Towner, E, Ward, H (2007). How exposure information can enhance our
understanding of child traffic "death leagues". Injury Prevention 13(2): 125-129.
46

Christie, N, Towner, E, Cairns, S, Ward, H (2004). Children's road traffic safety: an international
survey of policy and practice. Road Safety Research Report No. 47. London, Department for
Transport.
Cooper, A, Wedderkopp, N, Jago, R, Kristensen, P, Moller, N, Froberg, K, Page, A, Andersen, L (2008).
Longitudinal associations of cycling to school with adolescent fitness. Preventive Medicine 47(3):
342-328.
Cooper, A, Wedderkopp, N, Wang, H, Andersen, L, Froberg, K, Page, A (2006). ACtive travel to school
and cardiovascular fitness in Danish children and adolescents. Medicine and Science in Sports and
Exercise 38(10): 1724-1731.
Cozens, P, Saville, G, Hillier, D (2005). Crime prevention through environmental design (CPTED):a
review and modern bibliography. Property Management 23(5): 328-56.
Davison, K, Werder, J, Lawson, C (2008). Children's active commuting to school: current knowledge
and future directions. Preventing Chronic Disease: Public Health Research, Practice and Policy
5(3): 1-11.
De Hartog, JJ, Boogaard, H, Nijland, H, Hoek, G (2010). Do the health benefits of cycling outweigh the
risks? Environmental Health Perspectives. doi: 10.1289/ehp.0901747. Available Online 30 June
2010.
Department for Transport (2008). Travel to school: personal travel factsheet. London, [UK]
Department for Transport.
Department of Climate Change and Energy Efficiency (2010). Australian National Greenhouse
Accounts. Canberra, Commonwealth of Australia.
Department of Health and Ageing (2004). Active kids are healthy kids: Australia's physical activity
recommendations for 5-12 year olds.
http://www.health.gov.au/internet/wcms/publishing.nsf/Content/phd-physical-activity-kids-pdfcnt.htm/$FILE/kids-phys.pdf.
Department of Health and Ageing (2008). 2007 Australian National Children's Nutrition and Physical
Activity Survey: main findings. Canberra, Department of Health and Ageing.
Department of Human Services (2007). 2006 Victorian Child Health and Wellbeing Survey Technical
Report. Additional analysis of children's modes of travel to and from school conducted by Jan
Garrard. Melbourne, Victorian Department of Human Services.
Department of the Environment, Climate Change, Energy and Water (2010). ACT Greenhouse Gas
Emissions, ACT Greenhouse Gas Inventory 2008.
http://www.environment.act.gov.au/__data/assets/pdf_file/0015/200175/ACT_Greenhouse_Gas
_Inventory_2008.pdf. Accessed 06/07/2011.
Dobbins, M, De Corby, K, Robeson, P, Husson, H, Tirilis, D (2009). School-based physical activity
programs for promoting physical activity and fitness in children and adolescents aged 6-18.
Cochrane Database Syst Rev(1): CD007651.
Dollman, J, Lewis, N (2007). Active transport to school as part of a broader habit of walking and
cycling among South Australian Youth. Pediatric Exercise Science 19(4): 436-43.
Dora, C, Phillips, M (2000). Transport, environment and health. Copenhagen, World Health
Organisation Regional Office for Europe.
Elvik, R (2009). The non-linearity of risk and the promotion of environmentally sustainable transport.
Accident Analysis and Prevention 41(4): 849-55.
Environmental Protection Authority (2007). Noise surveys 2007. Melbourne, EPA.
Ewing, R, Brownson, RC, Berrigan, D (2006). Relationship Between Urban Sprawl and Weight of
United States Youth. American Journal of Preventive Medicine 31(6): 464-474.
Fry, D (2008). New South Wales Travelsmart Schools Program 2006-2007. Sydney, Sydney South
West Area Health Service.
Garrard, G, Rissel, C, Bauman, A (2011, in press). Cycling and health Cycling for sustainable transport:
international trends and policies. J Pucher & PJ Buehler, MIT Press.
Garrard, J (2010). Active school travel research project: final report. Melbourne, Unpublished report.
47

Garrard, J (2009). Active transport: children and young people. An overview of recent evidence.
Melbourne, Victorian Health Promotion Foundation.
Garrard, J, Crawford, S, Godbold, T (2009). Evaluation of the Ride2School Program: final report.
Melbourne, Deakin University.
Gauderman, WJ, Avol, E, Gilliland, F, Vora, H, Thomas, D, Berhane, K, McConnell, R, Kuenzli, N,
Lurmann, F, Rappaport, E, Margolis, H, Bates, D, Peters, J (2004). The effect of air pollution on
lung development from 10 to 18 years of age. The New England Journal Of Medicine 351(11):
1057-1067.
Gebel, K, King, L, Bauman, A, Vita, P, Gill, T, Rigby, A, Capon, A (2005). Creating healthy
environments: A review of links between the physical environment, physical activity and obesity.
Sydney, NSW Health Department and NSW Centre for Overweight and Obesity.
Hamer, M, Stamatakis, E, Mishra, G (2009). Psychological Distress, Television Viewing, and Physical
Activity in Children Aged 4 to 12 Years. Pediatrics 123(5): 1263-1268.
Hart, J (2008). Driven to excess: impacts of motor vehicle traffic on residentail quality of life in
Bristol, UK. MSc in Transport Planning at the University of the West of England, Bristol.
Hillier, B, Sahbaz, O (2006). High resolution analysis of crime patterns in urban street networks: an
initial statistical sketch from an ongoing study of a London Borough. London, University College
London.
Hillman, M (1993). One false move...An overview of the findings and issues they raise. Children,
transport and the quality of life. M. Hillman. London, Policy Studies Institute.
Hillman, M, Adams, J, Whitelegg, J (1990). One false move: a study of children's independent
mobility. London, Policy Studies Institute.
Hinkson, E, Duncan, S, Kearns, R, Badland, H (2008). 2008 School Travel Plan Evaluation: 2007 School
Year. Auckland, Auckland Regional Transport Authority.
Horton, D (2007). Fear of cycling. Cycling and society. D. Horton, P. Rosen and P. Cox. (Eds)
Hampshire, Ashgate Publishing: 133-52.
Hosking, J, Macmillan, A, Connor, J, Bullen, C, Ameratunga, S (2010). Organisational travel plans for
improving health. Cochrane Database of Systematic Reviews Mar 17;3:CD005575.
Ironmonger, D, Norman, P (2007). Travel behaviour of women, men and children: what changes and
what stays the same? Conference name. Conference location. From
Jacobsen, PL, Racioppi, F, Rutter, H (2009). Who owns the roads? How motorised traffic discourages
walking and cycling. Injury Prevention 15(6): 369-73.
Jensen, SU, Hummer, CH (2003). Safer routes to Danish schools. Sustainable transport: planning for
walking and cycling in urban environments. R. Tolley. Cambridge, England, Woodhead Publishing
Limited: 588-598.
Kelty, SF, Giles-Corti, B, Zubrick, SR (2008). Physical activity and young people: the impact of the built
environment in encouraging play, fun, and being active. Physical activity and children: new
research. N. P. Beaulieu. New York, Nova Science Publishers, Inc.: 7-33.
Ker, I (2009). Review of the Western Australia Walking School Bus Program. . Perth, CATALYST FOR
Department for Planning and Infrastructure.
Knox, EG (2006). Roads, railways, and childhood cancers. J Epidemiol Community Health 60(2): 136-
141.
Landsberg, B, Plachta-Danielzik, S, Much, D, Johannsen, M, Lange, D, Müller, M (2008). Associations
between active commuting to school, fat mass and lifestyle factors in adolescents: the Kiel
Obesity Prevention Study (KOPS)Associations between active commuting and fat mass. European
Journal of Clinical Nutrition 62: 739-747.
Lee, MC, Orenstein, MR, Richardson, MJ (2008). Systematic Review of Active Commuting to School
and Children’s Physical Activity and Weight. Journal of Physical Activity and Health 5(6): 930-949.
Litman, T (2009). Community cohesion as a transport planning objective, Victoria Transport Policy
Institute.
48

Litman, TA, Doherty, E (2009). Transportation cost and benefit analysis: techniques, estimates and
implications. Canada, Victorian Transport Policy Institute.
Malone, K (2007). The bubble-wrap generation: children growing up in walled gardens.
Environmental Education Research 13(4): 513-527.
Matthews, B, Bennell, K, McKay, H, Khan, K, Baxter-Jones, A, Mirwald, R (2006). Dancing for bone
health: a 3-year longitudinal study of bone mineral accrual across puberty in female non-elite
dancers and controls. Osteoporosis International 17: 1043-54.
Matthews, C, Jurj, A, Shu, X, Li, H, Yang, G, Li, Q, Gao, Y, Zheng, W (2007). Influence of exercise,
walking, cycling, and overall nonexercise physical activity on mortality in Chinese women.
American Journal of Epidemiology 165(12): 1343-1350.
McDonald, N, Deakin, E, Aalborg, A (2010). Influence of the social environment on children's school
travel. Preventive Medicine 50: S65-S68.
McKenzie-Mohr, D, Smith, W (1999). Fostering Sustainable Behavior: An Introduction to Community-
Based Social Marketing. Canada, New Society Publishers.
Ministry of Transport Public Works and Water Management (2009). Cycling in the Netherlands.
Utrecht, Ministry of Transport Public Works and Water Management.
Moodie, M, Haby, M, Galvin, L, Swinburn, B, Carter, R (2009). Cost-effectiveness of active transport
for primary school children - Walking School Bus program. Int J Behav Nutr Phys Act. 6: 63.
Morris, J, Wang, F, Lilja, L (nd). School Children’s Travel Patterns – A Look Back and A Way Forward.
Melbourne, Transport Research Centre, RMIT University.
Möser, G, Bamberg, S (2008). The effectiveness of soft transport policy measures: A critical
assessment and meta-analysis of empirical evidence. Journal of Environmental Psychology 28(1):
10-26.
Ogilvie, D, Foster, CE, Rothnie, H, Cavill, N, Hamilton, V, Fitzsimons, CF, Mutrie, N (2007).
Interventions to promote walking: systematic review. BMJ 334(7605): 1204.
Olds, T, Ridley, K, Tomkinson, G (2007). Declines in aerobic fitness: are they due only to increasing
fatness? Medicine and Sports Science 50: 226-240.
Panis, LI, deGeus, B, Vandenbulcke, G, Willems, H, Degraeuwe, B, Bleux, N, Mishra, V, Thomas, I,
Meeusen, R (2010). Exposure to particulate matter in traffic: A comparison of cyclists and car
passengers. Atmospheric Environment 44: 2263-70.
Pont, K, Ziviani, J, Wadley, D, Bennett, S, Abbott, R (2009). Environmental correlates of children's
active transportation: a systematic literature review. Health & Place 15: 849-862.
Population Health Research Centre ACT Health (2007). Report on the ACT Year 6 Physical Activity
and Nutrition Survey (ACTPANS), Health Series Number 43. Canberra, ACT Government.
Prezza, M, Alparone, F, Cristallo, C, Luigi, S (2005). Parental perception of social risk and of positive
potentiality of outdoor autonomy for children: the development of two instruments. Journal of
Environmental Psychology 25: 437-453.
Pucher, J, Buehler, R (2008). Making Cycling Irresistible: Lessons from The Netherlands, Denmark and
Germany. Transport Reviews 28(4): 495-528.
Pucher, J, Dill, J, Handy, S (2010). Infrastructure, programs and policies to increase bicycling: an
international review. Preventive Medicine 50(Jan Suppl 1): S106-25.
Rose, G (1999). A comprehensive evaluation of 'Safe Routes to School' implementation. Melbourne,
Institute of Transport Studies, Monash University.
Rosenbaum, M (1993). Independent mobility and children's rights. Children, transport and the
quality of life. M. Hillman. London, Policy Studies Institute.
Sallis, JF, Cervero, RB, Ascher, W, Henderson, KA, Kraft, MK, Kerr, J (2006). An ecological approach to
creating active living communities. Annu Rev Public Health 27: 297-322.
Salmon, J, Timperio, A, Cleland, V, Venn, A (2005). Trends in children's physical activity and weight
status in high and low socio-economic status areas of Melbourne, Victoria, 1985-2001. Australian
and New Zealand Journal of Public Health 29(4): 337-342.
49

Sibley, B, Etnier, J (2003). The relationship between physical activity and cognition in children: a
meta-analysis. Pediatric Exercise Science 15: 243-256.
Sirard, JR, Slater, ME (2008). Walking and bicycling to school: a review. American Journal of Lifestyle
Medicine 2(5): 372-396.
Skenazy, L (2009). Free-range kids: how to raise safe, self-reliant children. San Francisco, Jossey-Bass.
Sloman, L, Cavill, N, Cope, A, Muller, L, Kennedy, A (2009). Analysis and synthesis of evidence on the
effects of investment in six Cycling Demonstration Towns., Department for Transport and Cycling
England.
Slovic, P, Finucane, M, Peters, E, MacGregor, D (2004). Risk as analysis and risk as feelings: some
thoughts about affect, reason, risk, and rationality. Risk Analysis 24(2): 311-322.
Smith, A, McKenna, J, Duncan, R, Jonathan, L (2008). The impact of additional weekdays of active
commuting on children achieving a criterion of 300+ minutes of moderate-to-vigorous physical
activity. Australasian Association for Exercise and Sports Science Conference. Melbourne, March
2008.
Social Exclusion Unit (2003). Making the connections: final report on transport and social exclusion.
London, Office of the Deputy Prime Minister.
Sullivan, P, Percy, A (2008). Evaluating changes associated with workplace and school travel plans -
something old, something borrowed, something new. Conference name. Conference location.
From www.patrec.org/atrf/index.php?forum
The Obesity Society (nd). Obesity in Australian Children.
Thomson, L (2009). "How times have changed": active transport literature review. Melbourne,
VicHealth.
Tranter, P (1996). Children's independent mobility and urban form in Australasian, English and
German cities. World transport research proceedings of the 7th world conference on transport
research. D. Hensher, J. King and T. H. Oun. Oxford, Pergamon Press.
Tranter, P (2004). Effective speeds: car costs are slowing us down. Canberra, Australian Greenhouse
Office, Department of the Environment and Heritage. .
US Department of Health and Human Services (2008). Physical Activity Guidelines: Advisory
Committee Report 2008, US Department of Health and Human Services.
USA Interagency Working Group on Climate Change and Health 2009 (nd). A human health
perspective on climate change.
van der Ploeg, HP, Merom, D, Corpuz, G, Bauman, AE (2008). Trends in Australian children traveling
to school 1971-2003: Burning petrol or carbohydrates? Preventive Medicine 46(1): 60-62.
van Dyck, D, Cardon, G, Deforche, B, Bourdeaudhuij, ID (2009). Lower neighbourhood walkability and
longer distance to school are related to physical activity in Belgian adolescents. Preventive
Medicine 48: 516-518.
Vanderbilt, T (2008). Traffic: why we drive the way we do (and what it says about us). New York,
Alfred A Knopf.
Voss, C, Sandercock, G (2010). Aerobic fitness and mode of travel to school in English school
children. Medicine and Science in Sports and Exercise 42(2): 281-287.
Wen, LM, Fry, D, Merom, D, Rissel, C, Dirkis, H, Balafas, A (2008). Increasing active travel to school:
Are we on the right track? A cluster randomised controlled trial from Sydney, Australia.
Preventive Medicine 47(6): 612-618.
WHO (2008). Physical activity and young people. Geneva, World Health Organisation.
World Health Organisation: Regional Office for Europe (2011). Burden of disease from
environmental noise: quantification of healthy life years lost in Europe. Copenhagen, World
Health Organisation.
Yang, L, Sahlqvist, S, McMinn, A, Griffin, SJ, Ogilvie, D (2010). Interventions to promote cycling:
systematic review. BMJ 341(c5293).
50

Zubrick, S, Wood, L, Villanueva, K, Wood, G, Giles-Corti, B, Christian, H (2010). Nothing but fear itself:
parental fear as a determinant impacting on child physical activity and independent mobility.
Melbourne, Victorian Health Promotion Foundation.
51